In the remote sensing/aerial imaging industry, imagery is used to capture views of a geographic area and be able to measure objects and structures within the images as well as to be able to determine geographic locations of points within the image. These are generally referred to as “geo-referenced images” and come in two basic categories:                1. Captured Imagery—these images have the appearance as they were captured by the camera or sensor employed.        2. Projected Imagery—these images have been processed and converted such that they confirm to a mathematical projection.        
All imagery starts as captured imagery, but as most software cannot geo-reference captured imagery, that imagery is then reprocessed to create the projected imagery. The most common form of projected imagery is the ortho-rectified image. This process aligns the image to an orthogonal or rectilinear grid (composed of rectangles). The input image used to create an ortho-rectified image is a nadir image—that is, an image captured with the camera pointing straight down.
In addition to capturing an image with the camera pointing straight down, it is possible to capture an image with the camera pointing at an oblique angle. The resulting imagery is generally referred to as an “oblique image” or as an “oblique aerial image.” The capture of oblique aerial images presents additional challenges compared to the capture of nadir images, generally due to the introduction of the oblique angle.
An example of a system that captures both nadir and oblique images is shown in FIG. 1. Airplane 10 is flying over the Earth 12 and capturing images utilizing three cameras 14a, 14b and 14c. FIG. 1 also illustrates the sun 16 positioned in a northern hemisphere orientation. The camera 14a is shown directed in a southern orientation generally towards the sun 16, the camera 14b is shown directed straight down, and the camera 14c is shown directed in a northern orientation generally away from the sun 16. The cameras 14a and 14c capture “oblique images”, while the camera 14b captures “nadir images”.
The oblique images present a more natural appearance than a nadir image because they show not just the roofs, as is the case of a nadir image, but also the sides of objects and structures. This is what we are most accustomed to seeing. In order to preserve this natural perspective, oblique images are generally presented without being ortho-rectified and instead left in the natural appearance that the camera captures. This practice makes it very easy for people to look at something in an oblique image and realize what that object is.
However, the sun/sky orientation when an oblique image is taken has a major impact on the color balance of the resulting photograph due to the reflections of light from the sun 16. There are two major types of reflection: diffuse and specular. Flat wall paint is a highly diffuse reflector—that is, light bounces nearly equally in all directions. A mirror is a highly specular reflector—that is, light bounces almost entirely in one direction off the mirror. There is nothing in nature that is a perfect specular or a perfect diffuse reflector—everything is some combination of the two. It is the specular nature of objects that presents a problem for color balancing oblique images.
Color balancing nadir aerial images is known in the art. However, color balancing oblique aerial images presents unique challenges. When collecting nadir images (images captured with camera 14b pointing straight down), every image has a consistent orientation with respect to the sun 16. However, when collecting oblique images (images captured with the cameras 14a and 14c pointing at an oblique angle relative to the horizon) different images have different orientations with respect to the sun 16. For instance, in the northern hemisphere, a camera aimed to the north (camera 14c) points away from the sun 16, while a camera aimed to the south (camera 14a) points toward the sun 16.
Specular reflections bounce off a surface and leave the surface at roughly the same angle with which they hit the surface—like a ball bouncing off a flat surface. When the camera 14a is pointing towards the sun 16, the camera 14a picks up specular reflections from the sun 16 and therefore any images captured with that camera pick up a strong yellow/red tint to the captured scene. The camera 14c, on the other hand, is pointing away from the sun 16 and picks up specular reflections from the sky and therefore any images captured with that camera pick up a strong blue tint to the scene. When these two images are viewed side by side, the difference can be very noticeable and distracting to the overall image appearance. It is desirable to color balance the oblique images such that they have a substantially consistent color tone.
Shown in FIG. 2 is a diagrammatic view of the capturing of three different overlapping images of a same scene from three different positions. The three different positions are labeled as Position A, Position B and Position C for purposes of clarity. The scene is positioned in the northern hemisphere, and thus, the image captured from Position A is taken with the camera positioned in a southern orientation toward the sun 16, while the image captured from Position C is taken with the camera positioned in a northern orientation away from the sun 16. The image captured from Position B is taken with the camera positioned directly above the scene. In this example, the image captured from Position A has a yellow/reddish tint due to the strong specular reflections from the sun 16, the image captured from Position B has a neutral tint due to roughly equal specular reflections from the sun 16 and sky, and the image captured from Position C has a bluish tint due to the strong specular reflections from the sky.
Referring to FIG. 3, shown therein is a diagrammatic view of the capturing of an oblique image of the Earth 12 where a field of view of the camera is designated with the lines P1 and P2. The lines P1 and P2 represent path lengths, i.e., the distance the light travels from a scene on the Earth 12 to the camera. In an oblique image, the path lengths P1 and P2 are significantly different and this presents a second challenge to color balancing oblique images: the top of the image goes through significantly more atmosphere than the bottom of the image. In a nadir image, path length (the distance the light must travel from a scene on the Earth 12 to the camera) at the edges of the useable image are typically not all that much different than the path length to the nadir point. For instance, lines P3 and P4 represent the path lengths for a typical camera/lens configuration, the difference between the shortest path length (straight down) and the longest path length (to the far corner) is only about 6%.
But with oblique images, because of the nature of trigonometry, when the field of view angle is added to the oblique camera axis angle, the path lengths P1 and P2 are very different. To illustrate an extreme, if the top of the camera is pointed above the horizon then the path length P1 is infinite—clearly much longer than the path length P2 at the front of the image. In a typical camera/lens configuration and at a typical oblique angle, the difference between the shortest path length (to the middle front of the image) and the longest path length (to the far back corner of the image) is about 87%—nearly twice as long.
The challenge this difference in path length presents is that the light from the scene captured by the top of the camera travels through a lot more atmosphere than the light from the scene captured by the bottom of the camera. This results in more tinting or scattering, an increased introduction of blue sky light, an increase in blurriness, and a decrease in clarity due to smog or haze. Thus, if the image is color balanced based upon the tinting in the top of the image then the color balancing of the bottom of the image will be incorrect. Likewise, if the image is color-balanced based upon the tinting in the bottom of the image then the color-balancing of the top of the image will be incorrect. One could color-balance based upon the tinting in the middle of the image, but then the color-balancing of the top and bottom of the image would be incorrect.
In light of the foregoing, there is a need for a system and process for color-balancing oblique images that overcomes the challenges discussed above. It is to such a system and process that the present invention is directed.